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FINAL EXAM TOPIC LIST
Chapter 1
Population vs Sample
Chapter 2
Measures of Central Tendency:
– Mean, Median and Mode - be able to compute these, what do they measure (properties)
Measures of Variability:
– Standard Deviation (Variance) - be able to compute, what does it measure
Measures of Relative Standing:
– Percentile and z-Score - what do they measure, how are they interpreted
Chapter 3
Terms to understand: Sample Point, Sample Space, Event, Union, Intersection, and Complement
Complement Law, Additive Law and Multipicative Law - know what they say, be able to apply them
Conditional Probability, Independence, Mutually Exclusive and Combinations - know what they mean
and how to apply them
Chapter 4
Binomial Random Variable:
– What are its Characteristics
– Know how to use its Probability Distribution
– Understand the use of its Mean and Standard Deviation (Variance)
Chapter 5
What is the role of the standard normal distribution - how do we use the tables of a standard normal
to evaluate its probabilities
How is the standard normal distribution used to evaluate probabilities for a quantity that has any
normal ditribution - be able to evaluate probabilities and work word problems for normal random
variables
Chapter 6
What is a sampling distribution - how is it useful - what does the Central Limit Theorem say - be able
to apply it in a word problem
Chapter 7
What is the proper interpretation of a confidence interval
What is the point estimate of the population mean
How do we construct a confidence interval for a population mean when the sample size is large
How do we construct a confidence interval for a population mean when the sample size is not large -
(what assumption is made about the population when the sample size is small)
What is the point estimate for a population proportion
How do we construct a confidence interval for the population proportion when the sample size is large
Chapter 8
Tests of Hypotheses - null hypothesis, alternative hypothesis, type I error, type II error, test statistic,
rejection region, significance level, use and interpretation of a p-value, proper wording of conclusions
in a test of hypothesis
Formulate and conduct a test of hypothesis about a population mean when n is large and when n is
not large (what assumption is made in the latter case)
Formulate and conduct a test of hypothesis about a population proportion when n is large
Be able to compute and interpret a p-value for a large n problem setting
Chapter 9
When the two samples are independent, find a confidence interval for or conduct a test of hypothesis
about the difference between two population means ( ) when both sample sizes and are
large.
When the two samples are independent, find a confidence interval for or conduct a test of hypothesis
about the difference between two population means ( ) when one or both sample sizes and
are not large (what assumptions are made about the two populations in this case)
When the two samples are independent, find a confidence interval for or conduct a test of hypothesis
about the difference between two population proportions (
) when both sample sizes and are large
Find a confidence interval for or conduct a test of hypothesis about the difference between two population means (
) when the observations come from a paired data setting - when should we use
a paired data analysis, ie what is the purpose of pairing
Chapter 11
What are the roles of the dependent and independent variables - interpret the slope and intercept
What is the criterion for fitting the line - be able to find the best line and use it for prediction
What is the model and how is estimated?
How do we determine whether x is a useful linear predictor of y? - Be able to conduct this test
What is the difference between estimating the average response at a particular x-value and predicting a response at that x-value? - What is the source of extra variability in the prediction interval? Be able to construct these intervals
What does correlation represent - how is it measured - what is its unit of measurement - how is interpreted